Expression estimation and eQTL mapping for HLA genes with a personalized pipeline.

Area of Science:

• Genomics and Bioinformatics
• Immunogenetics
• Molecular Biology

Background:

• Human Leukocyte Antigen (HLA) genes are crucial for immune response and disease association, exhibiting high polymorphism.
• Understanding HLA gene expression patterns is vital for disease susceptibility and resistance, but accurate quantification is challenging due to genetic variability.
• Existing methods struggle with mapping short reads from highly polymorphic HLA loci and accounting for paralogous genes.

Purpose of the Study:

• To develop and validate a computational pipeline for accurate estimation of HLA gene expression using RNA-sequencing (RNA-seq) data.
• To improve both locus-level and allele-level expression quantification for HLA genes.
• To assess the impact of an HLA-personalized approach on downstream analyses, particularly eQTL mapping.

Main Methods:

• Development of a computational pipeline involving read alignment to all known HLA sequences for genotype inference.
• Quantification of gene expression using a personalized index based on inferred HLA genotypes.
• Application of the pipeline to the GEUVADIS dataset and comparison with standard reference transcriptome methods; simulations used to validate accuracy.

Main Results:

• The developed pipeline accurately estimates HLA gene expression, improving locus-level and allele-level quantification.
• While generally similar to reference transcriptome methods (r ≥ 0.87), the personalized pipeline showed differences for HLA-DQA1.
• The HLA-personalized approach enhanced eQTL mapping by improving p-values and causality compared to using a reference transcriptome.

Conclusions:

• The HLA-personalized computational pipeline provides a more accurate method for quantifying HLA gene expression from RNA-seq data.
• This improved quantification positively impacts downstream analyses, especially for identifying expression quantitative trait loci (eQTLs).
• The findings contribute to a better understanding of HLA gene regulation and its role in disease susceptibility and resistance.